Neural interface systems are typically implantable devices that are placed into biological tissue (e.g., brain or other neural tissue) and have the ability to record and/or stimulate the tissue through electrode sites. For example, neural interface systems may be strategically positioned in the brain (such as the cerebral cortex or in intracortical tissue) to record neural signals. However, there are several issues with current conventional neural interface systems. In long-term applications, conventional implantable neural interface systems have less-than-optimal reliability and reduced longevity due to degradation of the implanted device over time, thereby reducing the usability of the device. Furthermore, many of these implanted neural interface systems can cause potentially significant tissue trauma to the patient. The tissue trauma can cause neural signal degradation due to both acute and chronic tissue responses to the implant, such as local neuronal loss, increased tissue encapsulation, and other reactions to tissue trauma caused by the implantation. The acute and chronic tissue responses can negatively impact the usability of the neural device once implanted in the tissue. Thus, there is a need in the neural interface field to create a new and useful hybrid clustered neural interface system.